IOVS4NeRF:Incremental Optimal View Selection for Large-Scale NeRFs
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866917924031168512 |
|---|---|
| author | Xie, Jingpeng Tan, Shiyu Wang, Yuanlei Du, Tianle Xue, Yifei Lao, Yizhen |
| author_facet | Xie, Jingpeng Tan, Shiyu Wang, Yuanlei Du, Tianle Xue, Yifei Lao, Yizhen |
| contents | Large-scale Neural Radiance Fields (NeRF) reconstructions are typically hindered by the requirement for extensive image datasets and substantial computational resources. This paper introduces IOVS4NeRF, a framework that employs an uncertainty-guided incremental optimal view selection strategy adaptable to various NeRF implementations. Specifically, by leveraging a hybrid uncertainty model that combines rendering and positional uncertainties, the proposed method calculates the most informative view from among the candidates, thereby enabling incremental optimization of scene reconstruction. Our detailed experiments demonstrate that IOVS4NeRF achieves high-fidelity NeRF reconstruction with minimal computational resources, making it suitable for large-scale scene applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_18611 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | IOVS4NeRF:Incremental Optimal View Selection for Large-Scale NeRFs Xie, Jingpeng Tan, Shiyu Wang, Yuanlei Du, Tianle Xue, Yifei Lao, Yizhen Computer Vision and Pattern Recognition Large-scale Neural Radiance Fields (NeRF) reconstructions are typically hindered by the requirement for extensive image datasets and substantial computational resources. This paper introduces IOVS4NeRF, a framework that employs an uncertainty-guided incremental optimal view selection strategy adaptable to various NeRF implementations. Specifically, by leveraging a hybrid uncertainty model that combines rendering and positional uncertainties, the proposed method calculates the most informative view from among the candidates, thereby enabling incremental optimization of scene reconstruction. Our detailed experiments demonstrate that IOVS4NeRF achieves high-fidelity NeRF reconstruction with minimal computational resources, making it suitable for large-scale scene applications. |
| title | IOVS4NeRF:Incremental Optimal View Selection for Large-Scale NeRFs |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2407.18611 |